Fast, accurate evaluation of the dynamics parameters is a key ingredient for accurate control, estimation, and simulation of robots. As these are time-consuming to compute by hand, a software library for generating the rigid body dynamics symbolically can be of great use for robotics researchers. In this paper, we propose a library to efficiently compute and evaluate robot dynamics and its derivatives. Based on a URDF description of the robot's kinematics, three major rigid body dynamics algorithms are used to retrieve the dynamics symbolically in the CasADi framework. To validate the numerical accuracy, the numerical evaluation of the solutions are compared against three other well-established rigid body dynamics libraries, namely RBDL, KDL, and PyBullet. We conduct a timing comparison between the libraries, and we show that the evaluation times of the symbolic expressions are at most one order of magnitude higher than the evaluation times of the numerical libraries. Last, it is shown that the evaluation times of the dynamics derivatives remain of the same order as the evaluation times of the dynamics expressions.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.